Work

CEoptim: Cross-Entropy R Package for Optimization

Year: 2015

Type: preprint

Abstract: The cross-entropy (CE) method is simple and versatile technique for optimization, based on Kullback-Leibler (or cross-entropy) minimization. The method can be applied to a wide range of optimization tasks, including continuous, discrete, mixed and constrained optimization problems. The new package CEoptim provides the R implementation of the CE method for optimization. We describe the general CE methodology for optimization and well as some useful modifications. The usage and efficacy of CEoptim is demonstrated through a variety of optimization examples, including model fitting, combinatorial optimization, and maximum likelihood estimation.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1503.01842

Authors: Benham, Tim, Duan, Qibin, Kroese, Dirk P., Liquet, Benoit

Institutions: The University of Queensland, Université de Pau et des Pays de l'Adour

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers

Award: G6719690533

OpenAlex ID: W2140809082

Cites: 10

Cited by: 1

Related to: 10